Jianli Ding, Juan Qu, Yongmeng Su, Yongfu Zhang
remote sensing model; wet index (W); modified soil adjusted vegetation index type (MSAVI); feature space
Soil salinization is one of the major causes for soil desertification and ecological degradation in arid region. Acquiring large-scale and high-precision soil salinization information in real or near-real time is critical for preventing and mitigating soil salinization. The study area is located in Weigan-Kuqa oasis on the northern margin of the Tarim Basin. By analyzing Landsat-TM satellite image and soil samples obtained from field survey, we intend to investigate the relationship between Wet Index (WI) and Modified Soil-adjusted Vegetation Index (MSAVI). These two indices are often regarded as very important land cover biophysical parameters that are strongly descriptive of soil salinization in a certain degree. The study proposes a concept of MSAVI-WI feature space and builds a soil salinity monitoring index (MWI) model based on the analysis. The results indicate that there is a strong correlation between the MWI and surface soil salinity (with an R-squared of 0.844). Monitoring soil salinization with MWI is more precise than the salt indexes commonly used in traditional remote sensing monitoring methods. Difference matrix analysis also suggests that MWI detects different degrees of soil salinity and the changes of different combination of the vegetation and soil moisture better in the study area. Additionally, this index has a clear biophysical meaning that is often well accepted and understood. The study suggests that MWI will be helpful to monitor and evaluate soil salinization in arid region on large scale.